93 lines
4.2 KiB
Markdown
93 lines
4.2 KiB
Markdown
---
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title: TOCS 2024 Digest
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venue: TOCS
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year: 2024
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date: '2024-01-01'
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tags: []
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paper_count: 8
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draft: false
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---
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8 papers selected.
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---
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### PMAlloc: A Holistic Approach to Improving Persistent Memory Allocation
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*Zheng Dang, Shuibing He, Xuechen Zhang, Peiyi Hong *et al.**
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**TL;DR** — PMAlloc redesigns persistent memory allocation end-to-end, co-optimizing the allocator's data structures, concurrency, and crash consistency to dramatically reduce allocation overhead.
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**Why notable** — Persistent memory is still poorly understood at the allocator level; this paper offers a rare holistic treatment that will inform future PM software stacks.
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### Boki: Towards Data Consistency and Fault Tolerance with Shared Logs in Stateful Serverless Computing
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*Zhipeng Jia, Emmett Witchel*
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**TL;DR** — Boki introduces a shared-log abstraction for serverless functions that provides strong consistency and fault tolerance without requiring developers to manage state explicitly.
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**Why notable** — It reframes stateful serverless as a log-centric problem, offering a clean systems primitive that substantially simplifies correctness guarantees in function-as-a-service platforms.
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---
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### Diciclo: Flexible User-level Services for Efficient Multitenant Isolation
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*Giorgos Kappes, Stergios V. Anastasiadis*
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**TL;DR** — Diciclo provides a user-level framework that lets services customize their isolation mechanisms without kernel modifications, reducing interference among co-located tenants.
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**Why notable** — Multitenant isolation in cloud systems is typically a blunt instrument; this work shows that flexible, low-overhead isolation can be achieved entirely in user space.
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### SPATA: Effective OS Bug Detection with Summary-Based, Alias-Aware, and Path-Sensitive Typestate Analysis
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*Tuo Li, Jia-Ju Bai, Yulei Sui, Shi-Min Hu*
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**TL;DR** — SPATA applies a summary-based, alias-aware, and path-sensitive typestate analysis to detect resource-management bugs in OS kernels at scale.
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**Why notable** — Finding use-after-free and double-free bugs in OS code remains an open challenge; SPATA's precision improvements over prior static analyses make it a practical tool for kernel hardening.
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### Trinity: High-Performance and Reliable Mobile Emulation through Graphics Projection
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*Hao Lin, Zhenhua Li, Di Gao, Yunhao Liu *et al.**
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**TL;DR** — Trinity projects GPU rendering workloads from a mobile device onto a remote high-performance GPU, enabling faithful, high-throughput mobile emulation.
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**Why notable** — Mobile app testing at scale requires accurate emulation of GPU behavior; Trinity's graphics-projection design closes a long-standing fidelity gap in mobile emulators.
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### Optimizing Resource Management for Shared Microservices: A Scalable System Design
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*Shutian Luo, Chenyu Lin, Kejiang Ye, Guoyao Xu *et al.**
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**TL;DR** — This paper presents a scalable resource-management system for shared microservices that reduces interference and improves utilization in large-scale production deployments.
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**Why notable** — Microservice co-location is the norm in modern clouds, yet managing their shared resources at scale remains unsolved; this work delivers practical, production-validated answers.
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### Hardware-Software Collaborative Tiered-Memory Management Framework for Virtualization
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*Sai Sha, Chuandong Li, Xiaolin Wang, Zhenlin Wang *et al.**
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**TL;DR** — A hardware-software co-design framework that transparently manages hot/cold data placement across DRAM and slower memory tiers inside virtual machines.
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**Why notable** — As CXL-attached and NVM memory tiers become mainstream in data centers, principled tiered-memory management in hypervisors becomes critical; this paper provides a solid baseline.
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### Component-distinguishable Co-location and Resource Reclamation for High-throughput Computing
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*Laiping Zhao, Yushuai Cui, Yanan Yang, Xiaobo Zhou *et al.**
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**TL;DR** — This system differentiates micro-components of co-located workloads to reclaim idle resources precisely, boosting overall cluster throughput without violating SLOs.
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**Why notable** — Coarse-grained co-location wastes significant cluster capacity; the component-level granularity introduced here sets a new standard for resource-reclamation systems.
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